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Tomography and Purification of the Temporal-Mode Structure of Quantum Light

2018· article· en· W2784757986 on OpenAlexfundno aff
Vahid Ansari, John M. Donohue, Markus Allgaier, Linda Sansoni, Benjamin Brecht, Jonathan Roslund, Nicolas Treps, Georg Harder, Christine Silberhorn

Bibliographic record

VenuePhysical Review Letters · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaHorizon 2020 Framework ProgrammeLeibniz-GemeinschaftGottfried Wilhelm Leibniz Universität HannoverDeutsche Forschungsgemeinschaft
KeywordsQuantumPhotonPhysicsQuantum opticsBroadbandParametric statisticsQuantum stateMode (computer interface)Computer scienceQuantum imagingQuantum tomographyQuantum informationPulse (music)OpticsQuantum networkQuantum mechanicsMathematics

Abstract

fetched live from OpenAlex

High-dimensional quantum information processing promises capabilities beyond the current state of the art, but addressing individual information-carrying modes presents a significant experimental challenge. Here we demonstrate effective high-dimensional operations in the time-frequency domain of nonclassical light. We generate heralded photons with tailored temporal-mode structures through the pulse shaping of a broadband parametric down-conversion pump. We then implement a quantum pulse gate, enabled by dispersion-engineered sum-frequency generation, to project onto programmable temporal modes, reconstructing the quantum state in seven dimensions. We also manipulate the time-frequency structure by selectively removing temporal modes, explicitly demonstrating the effectiveness of engineered nonlinear processes for the mode-selective manipulation of quantum states.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.196

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.286
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations78
Published2018
Admission routes1
Has abstractyes

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